Robotically-induced auditory-verbal hallucinations: combining self-monitoring and strong perceptual priors.

BACKGROUND: Inducing hallucinations under controlled experimental conditions in non-hallucinating individuals represents a novel research avenue oriented toward understanding complex hallucinatory phenomena, avoiding confounds observed in patients. Auditory-verbal hallucinations (AVH) are one of the most common and distressing psychotic symptoms, whose etiology remains largely unknown. Two prominent accounts portray AVH either as a deficit in auditory-verbal self-monitoring, or as a result of overly strong perceptual priors. METHODS: In order to test both theoretical models and evaluate their potential integration, we developed a robotic procedure able to induce self-monitoring perturbations (consisting of sensorimotor conflicts between poking movements and corresponding tactile feedback) and a perceptual prior associated with otherness sensations (i.e. feeling the presence of a non-existing another person). RESULTS: Here, in two independent studies, we show that this robotic procedure led to AVH-like phenomena in healthy individuals, quantified as an increase in false alarm rate in a voice detection task. Robotically-induced AVH-like sensations were further associated with delusional ideation and to both AVH accounts. Specifically, a condition with stronger sensorimotor conflicts induced more AVH-like sensations (self-monitoring), while, in the otherness-related experimental condition, there were more AVH-like sensations when participants were detecting other-voice stimuli, compared to detecting self-voice stimuli (strong-priors). CONCLUSIONS: By demonstrating an experimental procedure able to induce AVH-like sensations in non-hallucinating individuals, we shed new light on AVH phenomenology, thereby integrating self-monitoring and strong-priors accounts.

KIOS: A smartphone app for self-monitoring for patients with bipolar disorder.

OBJECTIVES: This study examined the use of a self-monitoring/self-management smartphone application (app) for patients with bipolar disorder. The app was specifically designed with patient-centered computational software system based on concepts from nonlinear systems (chaos) theory. METHODS: This was a randomized, active comparator study of use of the KIOS app compared to an existing free app that has high utilization rates known as eMoods, over 52 weeks, and performed in three academic centers. Patients were evaluated monthly utilizing the Bipolar Inventory of Symptoms Schedule (BISS). The primary outcome measure was the persistence of using the app over the year of the study. RESULTS: Patients assigned to KIOS persisted in the study longer than those assigned to eMoods; 57 patients (87.70%) in the KIOS group versus 42 (73.69%) in the eMoods group completed the study (p = 0.03). By 52 weeks, significantly more of KIOS group (84.4%) versus eMoods group (54%) entered data into their programs (χ2 = 14.2, df = 1, p = 0.0002). Patient satisfaction for KIOS was greater (F = 5.21, df = 1, 108, p = 0.025) with a standardized effect size (Cohen's d) of 0.41. There was no difference in clinical outcome at the end of the study between the two groups. CONCLUSIONS: This is the first randomized comparison study comparing two apps for the self-monitoring/self-management of bipolar disorder. The study revealed greater patient satisfaction and greater adherence to a patient-centered software program (KIOS) than a monitoring program that does not provide feedback (eMoods).

Investigating the efficacy of digital cognitive behavioural therapy in comparison to a sleep-monitoring application via integrated diary and actigraphy: A randomised-controlled trial.

Dissemination of digital cognitive behavioural therapy is a promising approach for treating insomnia in the broad population. Current evidence supports the effectiveness of the digital format, but clinical findings are often limited by the choice of control group and lack of in-depth therapeutic measures. This study was designed to investigate the specific effects of digital cognitive behavioural therapy in comparison to a self-monitoring application. Participants meeting criteria for insomnia were randomly allocated (1:1) to 8 weeks of digital cognitive behavioural therapy or 8 weeks of digital sleep monitoring (control application). The primary outcome, insomnia severity, was assessed at baseline, 8- and 16-weeks post-randomisation. Secondary outcomes included the assessment of sleep via application-integrated sleep diaries and actigraphy. Linear-mixed models were fitted to assess between-group differences. Fifty-six participants (48 females, mean age: M = 45.55 ± 13.70 years) were randomised to either digital cognitive behavioural therapy (n = 29) or digital sleep monitoring (n = 27). At 8- and 16-weeks post-randomisation, large treatment effects (d = 0.87-1.08) indicated robust reductions (-3.70 and -2.97, respectively; p ≤ 0.003) in insomnia severity in the digital cognitive behavioural therapy arm, relative to digital sleep monitoring. Treatment effects in favour of digital cognitive behavioural therapy were also found for self-reported and actigraphy-derived sleep continuity variables, indicating that sleep improved throughout the 8-week intervention period. Our study reinforces the role of digital cognitive behavioural therapy in achieving clinical improvements for patients with insomnia, affirming previous findings and supporting the specific effects of cognitive behavioural therapy.

Effects of continuous glucose monitoring on glycaemic control in type 2 diabetes: A systematic review and network meta-analysis of randomized controlled trials.

AIMS: The aim of this study was to assess the efficacy of continuous glucose monitoring (CGM) versus self-monitoring of blood glucose (SMBG) in maintaining glycaemic control among people with type 2 diabetes mellitus (T2DM). MATERIALS AND METHODS: The protocol was registered in PROSPERO (CRD42023387583). PubMed, Web of Science, EMBASE and OVID databases were searched from 1 January 2000 until 31 December 2022 for randomized controlled trials comparing CGM with SMBG in glycaemic control among the outpatients with T2DM. The primary endpoint was glycated haemoglobin, while the secondary endpoints included time in range, time below range and time above range. Both traditional and network meta-analyses were conducted to explore the efficacy of CGM on glycaemic control in T2DM. RESULTS: Eleven high-quality studies, involving 1425 individuals with T2DM, were identified. Traditional meta-analysis revealed that CGM exhibited a significantly decreased [mean difference (MD): -0.31, 95% confidence interval (CI) (-0.45, -0.18)], time above range [MD: -9.06%, 95% CI (-16.00, -2.11)], time below range [MD: -0.30%, 95% CI (-0.49, -0.12)] and a significantly increased time in range [MD: 8.49%, 95% CI (3.96, 13.02)] compared with SMBG. The network meta-analysis showed that real-time CGM can improve the glycaemic control of patients with T2DM to the most extent. CONCLUSIONS: CGM could provide T2DM with greater benefits in glycaemic management compared with SMBG, particularly in patients using real-time CGM. These findings provide an updated perspective on previous research and offer guidance for CGM use in T2DM.

Impact of feedback generation and presentation on self-monitoring behaviors, dietary intake, physical activity, and weight: a systematic review and meta-analysis.

Self-monitoring of dietary intake, physical activity, and weight is a key strategy in behavioral interventions, and some interventions provide self-monitoring feedback to facilitate goal setting and promote engagement. This systematic review aimed to evaluate whether feedback increases intervention effectiveness, and which forms of feedback presentation (e.g., personalized vs. not personalized) and generation (i.e., human vs. algorithm-generated) are most effective. To achieve this aim, 5 electronic databases (PubMed/MEDLINE, Web of Science, CINAHL, PsycINFO, and Google Scholar) were searched in April 2022 and yielded 694 unique records, out of which 24 articles reporting on 19 studies were included (with a total of 3261 participants). Two reviewers independently screened titles and abstracts and then full texts and categorized articles as eligible or excluded according to the pre-registered criteria (i.e., availability of full text, peer reviewed manuscript in English; adult participants in a randomized controlled trial that included both self-monitoring and feedback; comparisons of different forms of feedback or comparisons of feedback vs. no feedback; primary outcomes of diet, physical activity, self-monitoring behavior, and/or weight). All included studies were assessed for methodological quality independently by two reviewers using the revised Cochrane risk-of-bias tool for randomized studies (version 2). Ten studies compared feedback to no feedback, 5 compared human- vs. algorithm-generated feedback, and the remaining 4 studies compared formats of feedback presentation (e.g., frequency, richness). A random effects meta-analysis indicated that physical activity interventions with feedback provision were more effective than physical activity interventions without feedback (d = 0.73, 95% CI [0.09;1.37]). No meta-analysis could be conducted for other comparisons due to heterogeneity of study designs and outcomes. There were mixed results regarding which form of feedback generation and presentation is superior. Limitations of the evidence included in this review were: lack of details about feedback provided, the brevity of most interventions, the exclusion of studies that did not isolate feedback when testing intervention packages, and the high risk of bias in many studies. This systematic review underlines the importance of including feedback in behavioral interventions; however, more research is needed to identify most effective forms of feedback generation and presentation to maximize intervention effectiveness.Trial registration (PROSPERO)CRD42022316206.

Leveraging continuous glucose monitoring as a catalyst for behaviour change: a scoping review.

BACKGROUND: Amidst the escalating prevalence of glucose-related chronic diseases, the advancements, potential uses, and growing accessibility of continuous glucose monitors (CGM) have piqued the interest of healthcare providers, consumers, and health behaviour researchers. Yet, there is a paucity of literature characterising the use of CGM in behavioural intervention research. This scoping review aims to describe targeted populations, health behaviours, health-related outcomes, and CGM protocols in randomised controlled trials (RCTs) that employed CGM to support health behaviour change. METHODS: We searched Ovid MEDLINE, Elsevier Embase, Cochrane Central Register of Controlled Trials, EBSCOhost PsycINFO, and ProQuest Dissertations & Theses Global from inception to January 2024 for RCTs of behavioural interventions conducted in adults that incorporated CGM-based biological feedback. Citation searching was also performed. The review protocol was registered ( https://doi.org/10.17605/OSF.IO/SJREA ). FINDINGS: Collectively, 5389 citations were obtained from databases and citation searching, 3995 articles were screened, and 31 were deemed eligible and included in the review. Most studies (n = 20/31, 65%) included adults with type 2 diabetes and reported HbA1c as an outcome (n = 29/31, 94%). CGM was most commonly used in interventions to target changes in diet (n = 27/31, 87%) and/or physical activity (n = 16/31, 52%). 42% (n = 13/31) of studies provided prospective CGM-based guidance on diet or activity, while 61% (n = 19/31) included retrospective CGM-based guidance. CGM data was typically unblinded (n = 24/31, 77%) and CGM-based biological feedback was most often provided through the CGM and two-way communication (n = 12/31, 39%). Communication typically occurred in-person (n = 13/31, 42%) once per CGM wear (n = 13/31; 42%). CONCLUSIONS: This scoping review reveals a predominant focus on diabetes in CGM-based interventions, pointing out a research gap in its wider application for behaviour change. Future research should expand the evidence base to support the use of CGM as a behaviour change tool and establish best practices for its implementation. TRIAL REGISTRATION: doi.org/10.17605/OSF.IO/SJREA.

Goal pursuit increases more after dietary success than after dietary failure: examining conflicting theories of self-regulation using ecological momentary assessment.

BACKGROUND: Maintaining a healthy body weight and reaching long-term dietary goals requires ongoing self-monitoring and behavioral adjustments. How individuals respond to successes and failures is described in models of self-regulation: while cybernetic models propose that failures lead to increased self-regulatory efforts and successes permit a reduction of such efforts, motivational models (e.g., social-cognitive theory) make opposite predictions. Here, we tested these conflicting models in an ecological momentary assessment (EMA) context and explored whether effort adjustments are related to inter-individual differences in perceived self-regulatory success in dieting (i.e., weight management). METHODS: Using linear mixed effects models, we tested in 174 diet-interested individuals whether current day dietary success or failure (e.g., on Monday) was followed by self-regulatory effort adjustment for the next day (e.g., on Tuesday) across 14 days. Success vs. failure was operationalized with two EMA items: first, whether food intake was higher vs. lower than usual and second, whether food intake was perceived as more vs. less goal-congruent than usual. Trait-level perceived self-regulatory success in dieting was measured on a questionnaire. RESULTS: Intended self-regulatory effort increased more strongly after days with dietary success (i.e., eating less than usual / rating intake as goal-congruent) than after days with dietary failure (i.e., eating more than usual / rating intake as goal-incongruent), especially in those individuals with lower scores on perceived self-regulatory success in dieting. CONCLUSIONS: Findings support mechanisms proposed by social-cognitive theory, especially in unsuccessful dieters. Thus, future dietary interventions could focus on preventing the decrease in self-regulatory effort after instances of dietary failures and thereby mitigate the potential risk that a single dietary failure initiates a downward spiral into unhealthy eating.

The SElf-Care After REnal Transplantation Study: A Retrospective Evaluation of a Home-Monitoring Program Implemented as Standard Care.

After transplantation self-management is essential for graft survival and optimal quality of life. To address the need for home-based support in self-management, we implemented the "SelfCare after Renal Transplantation" (SeCReT) box, containing home-monitoring equipment combined with a smartphone application that was linked to the electronic patient records. This study investigated the uptake and continuation, protocol adherence, and subjective evaluation of this home-monitoring program. All "de novo" kidney recipients who received the SeCReT-box in the study period (Aug 2021-Dec 2022) were eligible for inclusion. Protocol adherence was defined as ≥75%. Subjective evaluation was assessed with a 5-item questionnaire. Of the 297 recipients transplanted, 178 participants (60%) were included in the analysis. Protocol adherence was 83%, 73%, 66%, and 57% respectively at 5, 10, 20, and 40 weeks of the protocol. With regard to continuation, 135 participants were still in the program at the end of the study period (75% retention rate). Regarding subjective evaluations, 82% evaluated the program positively, and 52% reported lower care needs due to home-monitoring. Results are positive among those who entered and continued the program. Qualitative research is needed on barriers to entering the program and facilitators of use in order to promote optimal implementation.

Digital health and wearable devices for retinal disease monitoring.

Digital health is wielding a growing influence across all areas of healthcare, encompassing various facets such as telemedicine, artificial intelligence (AI), and electronic healthcare records. In Ophthalmology, digital health innovations can be broadly divided into four categories: (i) self-monitoring home devices and apps, (ii) virtual and augmented reality visual aids, (iii) AI software, and (iv) wearables. Wearable devices can work in the background, collecting large amounts of objective data while we do our day-to-day activities, which may be ecologically more valid and meaningful to patients than that acquired in traditional hospital settings. They can be a watch, wristband, piece of clothing, glasses, cane, smartphone in our pocket, earphones, or any other device with a sensor that we carry with us. Focusing on retinal diseases, a key challenge in developing novel therapeutics has been to prove a meaningful benefit in patients' lives and the creation of objective patient-centred endpoints in clinical trials. In this review, we will discuss wearable devices collecting different aspects of visual behaviour, visual field, central vision, and functional vision, as well as their potential implementation as outcome measures in research/clinical trial settings. The healthcare landscape is facing a paradigm shift. Clinicians have a key role of collaborating with the development and fine-tuning of digital health innovations, as well as identifying opportunities where they can be leveraged to enhance our understanding of retinal diseases and improve patient outcomes.

The effects of gaze-display feedback on medical students' self-monitoring and learning in radiology.

Self-monitoring is essential for effectively regulating learning, but difficult in visual diagnostic tasks such as radiograph interpretation. Eye-tracking technology can visualize viewing behavior in gaze displays, thereby providing information about visual search and decision-making. We hypothesized that individually adaptive gaze-display feedback improves posttest performance and self-monitoring of medical students who learn to detect nodules in radiographs. We investigated the effects of: (1) Search displays, showing which part of the image was searched by the participant; and (2) Decision displays, showing which parts of the image received prolonged attention in 78 medical students. After a pretest and instruction, participants practiced identifying nodules in 16 cases under search-display, decision-display, or no feedback conditions (n = 26 per condition). A 10-case posttest, without feedback, was administered to assess learning outcomes. After each case, participants provided self-monitoring and confidence judgments. Afterward, participants reported on self-efficacy, perceived competence, feedback use, and perceived usefulness of the feedback. Bayesian analyses showed no benefits of gaze displays for post-test performance, monitoring accuracy (absolute difference between participants' estimated and their actual test performance), completeness of viewing behavior, self-efficacy, and perceived competence. Participants receiving search-displays reported greater feedback utilization than participants receiving decision-displays, and also found the feedback more useful when the gaze data displayed was precise and accurate. As the completeness of search was not related to posttest performance, search displays might not have been sufficiently informative to improve self-monitoring. Information from decision displays was rarely used to inform self-monitoring. Further research should address if and when gaze displays can support learning.

Feasibility of hand grip tests during and after hospitalization in geriatric patients: an observational study.

BACKGROUND: Monitoring the recovery trajectory during and after hospitalization can be a valuable method to observe whether additional care is needed to optimize recovery. Hand grip strength tests are commonly used to measure an individual's physical condition. Eforto® is a system to monitor hand grip strength and grip work as measures of recovery. We examined the feasibility of daily repeated hand grip tests measured with Eforto® in geriatric inpatients, during hospitalization and at home after discharge. METHODS: Geriatric inpatients (n = 191) were evaluated for grip strength and grip work with Eforto®, twice daily during their admission. We calculated attempt and success rates. Participants were divided into complete, high, moderate, and low attempt/success rate groups to study differences in patient characteristics. Reasons for non-attempt and unsuccessful tests were categorized and analyzed. Nine participants were interviewed about acceptability and user experience within the hospital setting. Four out of twenty participants accepted the invitation to continue the measurements after discharge at home for 4 weeks and were interviewed about acceptability and user experience. RESULTS: Across the 191 participants, the attempt rate was 85% and 86% of the attempted tests was successful. The main reasons for non-attempt were that the patient felt physically unwell (41%), and that the patient was otherwise engaged, for example receiving care or undergoing medical tests (40%). Measurements were unsuccessful mostly because of the patient not having enough strength to reach the 80% threshold needed for the grip work test (60%). Participants in the complete and high attempt/success rate groups had a shorter length of stay (p<0.05) and a lower mortality (p<0.05) than participants in the moderate/low groups. The interview data showed good acceptability and user experience during hospitalization. The acceptability was strengthened by experienced usefulness. Self-monitoring at home resulted in low inclusion rate (20%) and low success rate (25%), with the uncertain time after discharge from the hospital as the main barrier. CONCLUSIONS: For most patients, the tests were feasible in the supervised hospital setting. At-home testing with Eforto® is challenging, primarily because of the uncertain time after discharge from the hospital.

The experiences and perspectives of people with gout on urate self-monitoring.

INTRODUCTION: Gout management remains suboptimal despite safe and effective urate-lowering therapy. Self-monitoring of urate may improve gout management, however, the acceptability of urate self-monitoring by people with gout is unknown. The aim of this study was to explore the experiences of urate self-monitoring in people with gout. METHODS: Semistructured interviews were conducted with people taking urate-lowering therapy (N = 30) in a 12-month trial of urate self-monitoring in rural and urban Australia. Interviews covered the experience of monitoring and its effect on gout self-management. Deidentified transcripts were analysed thematically. RESULTS: Participants valued the ability to self-monitor and gain more understanding of urate control compared with the annual monitoring ordered by their doctors. Participants indicated that self-monitoring at home was easy, convenient and informed gout self-management behaviours such as dietary modifications, hydration, exercise and medication routines. Many participants self-monitored to understand urate concentration changes in response to feeling a gout flare was imminent or whether their behaviours, for example, alcohol intake, increased the risk of a gout flare. Urate concentrations were shared with doctors mainly when they were above target to seek management support, and this led to allopurinol dose increases in some cases. CONCLUSION: Urate self-monitoring was viewed by people with gout as convenient and useful for independent management of gout. They believed self-monitoring achieved better gout control with a less restricted lifestyle. Urate data was shared with doctors at the patient's discretion and helped inform clinical decisions, such as allopurinol dose changes. Further research on implementing urate self-monitoring in routine care would enable an evaluation of its impact on medication adherence and clinical outcomes, as well as inform gout management guidelines. PATIENT OR PUBLIC CONTRIBUTION: One person with gout, who was not a participant, was involved in the study design by providing feedback and pilot testing the semistructured interview guide. In response to their feedback, subsequent modifications to the interview guide were made to improve the understandability of the questions from a patient perspective. No additional questions were suggested.

Why more successful? An analysis of participants' self-monitoring data in an online weight loss intervention.

BACKGROUND: Self-monitoring is crucial for behavioral weight loss. However, few studies have examined the role of self-monitoring using mixed methods, which may hinder our understanding of its impact. METHODS: This study examined self-monitoring data from 61 Chinese adults who participated in a 5-week online group intervention for weight loss. Participants reported their baseline Body Mass Index (BMI), weight loss motivation, and engaged in both daily quantitative self-monitoring (e.g., caloric intake, mood, sedentary behavior, etc.) and qualitative self-monitoring (e.g., daily log that summarizes the progress of weight loss). The timeliness of participants' daily self-monitoring data filling was assessed using a scoring rule. One-way repeated measurement ANOVA was employed to analyze the dynamics of each self-monitoring indicator. Correlation and regression analyses were used to reveal the relationship between baseline data, self-monitoring indicators, and weight change. Content analysis was utilized to analyze participants' qualitative self-monitoring data. Participants were categorized into three groups based on their weight loss outcomes, and a chi-square test was used to compare the frequency distribution between these groups. RESULTS: After the intervention, participants achieved an average weight loss of 2.52 kg (SD = 1.36) and 3.99% (SD = 1.96%) of their initial weight. Daily caloric intake, weight loss satisfaction, frequency of daily log, and the speed of weight loss showed a downward trend, but daily sedentary time gradually increased. Moreover, regression analysis showed that baseline BMI, weight loss motivation, and timeliness of daily filling predicted final weight loss. Qualitative self-monitoring data analysis revealed four categories and nineteen subcategories. A significant difference in the frequency of qualitative data was observed, with the excellent group reporting a greater number of daily logs than expected in all categories and most subcategories, and the moderate and poor groups reporting less than expected in all categories and most subcategories. CONCLUSION: The self-monitoring data in short-term online group intervention exhibited fluctuations. Participants with higher baseline BMI, higher levels of weight loss motivation, and timely self-monitoring achieved more weight loss. Participants who achieved greater weight loss reported a higher quantity of qualitative self-monitoring data. Practitioners should focus on enhancing dieters' weight loss motivation and promote adherence to self-monitoring practices.

Evaluation of self-monitoring of blood pressure in the PERHIT study and the impact on glomerular function.

BACKGROUND: Although intensive blood pressure (BP) control has not been shown to slow the progression of chronic kidney disease (CKD), intensive BP control has been shown to reduce the risk for adverse cardiovascular outcomes in the CKD population. The aim of this post-hoc study was to study the interplay between a self-monitoring BP system and glomerular function. METHODS: In all, 949 participants with hypertension underwent visits at baseline, after eight weeks and 12 months. Half of the participants received a BP monitor and installed a program on their mobile phone. During eight weeks, they measured daily and reported their BP values. RESULTS: Within the intervention group, BP and systolic BP (SBP) decreased from baseline to eight weeks and 12 months (p < .001). Pulse pressure (PP) and mean arterial blood pressure (MAP) decreased from baseline to eight weeks (p = .021 and p = .004) vs 12 months (p = .035 and p = .008). Within the control group, a decrease was observed from baseline to 12 months for SBP, diastolic BP (DBP) and PP (p = .025, p = .023 and p = .036). In the intervention group, we observed an association between a decrease in SBP, DBP, PP and MAP and a decrease in eGFR (estimated glomerular filtration rate), (p < .001, p < .001, p = .013 and p < .001). In the control group, similar results were observed for PP only (p = .027). Within the intervention group, eGFR decreased (p < .001) but within the control group, the decrease was non-significant (p = .051). CONCLUSION: We observed an association between a decrease in all BP components and eGFR decline within the normal range in the intervention group but not in the controls. TRIAL REGISTRATION: The study was registered with ClinicalTrials.gov [NCT03554382].

WHAT IS THE CONTEXTHypertension is a common risk factor and has been identified as the most important contributor to end stage renal disease (ESRD)At present, it is unclear if hypertension also plays a role in the gradual loss of kidney function that occurs with ageing in the general populationSome studies have found a link between baseline blood pressure and a decline in GFR (glomerular filtration rate), while others have shown no relationship or even higher GFRMost patients with hypertension attend primary care for diagnosis, treatment and follow-up. Home blood pressure monitoring in hypertension treatment is becoming increasingly commonThe PERson-centredness in Hypertension management using Information Technology (PERHIT) study was designed to evaluate the effect of supporting self-management on (home) blood pressure by the use of information technology and aimed to lower blood pressure in patients with hypertension in primary careThe aim of this sub-study was to evaluate whether a person-centred approach in the treatment of high blood pressure, according to PERHIT, will have an impact on kidney function in patients with hypertension.WHAT IS NEWBlood pressure reduction in the intervention group was associated with a greater fall of eGFR (estimated GFR)glomerular filtration rate), but within the normal range, present already after eight weeks.Our analyses showed significant interactions between improved treatment related to the blood pressure components and lowering of eGFR, suggesting that the association between blood pressure changes and eGFR reduction was most prominent in individuals undergoing more effective antihypertensive treatment.WHAT IS THE IMPACTOur study concerns a common patient group at primary healthcare centres. When blood pressure treatment is initiated, or when treatment is increased via the general practitioner, it is common practice to arrange for a follow-up check of kidney function estimates such as creatinine and eGFR. In many cases, unfortunately not in accordance with proven science and experience, hypertension medication might be discontinued, or the dose reduced due to a short-term deterioration of kidney function (eGFR) that often reverts to normal levels again. This is a development that must be observed and prevented.Our results show that intensified blood pressure control is associated with a reduction in glomerular function measured by eGFR, but within normal range.

Exploring weight-related self-monitoring as a potential risk factor for eating disorder symptoms in adults - A systematic review and meta-analysis.

OBJECTIVE: Weight-related self-monitoring (WRSM), which involves the intentional tracking of body weight metrics, has been considered a potential risk factor for eating disorders. Therefore, the aim of this study was to systematically summarize the current state of the literature and to quantify the possible association between WRSM and eating disorder symptoms in adults. METHOD: Preregistration was carried out using PROSPERO (ID CRD42022366133). The PubMed, PsycInfo, and Web of Science databases were searched until December 21, 2023. A study had to be 1) be available in English or German, 2) be peer-reviewed and quantitative, 3) include adult participants (age ≥18 years) from the general population, 4) assess eating disorder symptoms via at least one of the following questionnaires: EDI, EAT, FEV, TFEQ, DEBQ, EDE-Q, Munich ED-Quest or IEG, and 5) include WRSM. Data analyses included descriptive analyses and three-level meta-analysis, corrected for correlations, for the global score and the different subscales of the eating disorder questionnaires. RESULTS: A total of 28 studies (n = 17,370 participants), with an overall fair methodological quality, were included in the systematic review. Out of these studies, nine studies with n = 13,507 participants were ultimately analyzed in the meta-analysis. The three-level meta-analysis did not reveal a significant association between WRSM and the eating disorder global score (r = 0.13, 95% CI [-0.02, 0.28]; p = 0.08), with this pattern also being evident in the subgroup analysis (diet monitoring). DISCUSSION: WRSM alone does not generally translate into an increased risk of disordered eating symptoms in the general population. We assume that individual factors are likely to determine whether the use of WRSM could lead to eating disorder symptoms. These factors should be accounted for in future research.

Correlation between centre size, metabolic variation and mean HbA1c in major paediatric diabetes centres.

AIM: To exploit a relatively homogeneous national health care context and a national diabetes database to address the questions: Is there an optimal clinic/centre size in determining outcomes?; and Can improvement in median centre outcomes be driven by reducing variability in outcome? METHODS: Using the Australasian Diabetes Database Network, data from seven tertiary hospital paediatric diabetes clinics for patients with type one diabetes from Australia were recorded from 6-month uploads: September 2017, March 2018, September 2018 and March 2019. Data from 25 244 patient visits included demographic variables, HbA1C, number of patient visits and insulin regimens. RESULTS: There was no association between centre size and median HbA1C. On the other hand, there was a significant association between or median absolute deviation of HbA1C outcomes and the median HbA1C result between centres. On average every two thirds of a median absolute deviation increase in clinic HbA1C was associated with a 1.0% (10.9 mmol/mol) increase in median clinic HbA1C. CONCLUSIONS: Our data have shown that it is likely difficult for centres to have a low median HbA1C if there is high variance of HbA1C's within centres or within centre treatment groups. This appears to be true regardless of centre size. These findings need to be carefully considered by teams who wish to lower their clinic median HbA1C.

Error traps in the perioperative management of children with type 1 diabetes.

Patients with type 1 diabetes mellitus (T1D) require insulin administration at all times to maintain euglycemia and metabolic stability. Insulin administration in the perioperative period is complicated by fasting requirements and perioperative stressors that can change the patient's insulin needs. In addition, many anesthesia providers are not familiar with insulin dosing strategies and technology, such as insulin pumps and continuous glucose monitors (CGMs), that are commonly used by patients with T1D. Errors in perioperative insulin administration can lead to hypoglycemia, hyperglycemia, and diabetic ketoacidosis. This article reviews common errors of associated with the perioperative management of patients with T1D, including failure to assess and coordinate patient care preoperatively; failure to understand diabetes management and technology; failure to monitor blood glucose and recognize dysglycemia; and failure to appropriately administer basal insulin.

Understanding Heterogeneity in Individual Responses to Digital Lifestyle Intervention Through Self-Monitoring Adherence Trajectories in Adults With Overweight or Obesity: Secondary Analysis of a 6-Month Randomized Controlled Trial.

BACKGROUND: Achieving clinically significant weight loss through lifestyle interventions for obesity management is challenging for most individuals. Improving intervention effectiveness involves early identification of intervention nonresponders and providing them with timely, tailored interventions. Early and frequent self-monitoring (SM) adherence predicts later weight loss success, making it a potential indicator for identifying nonresponders in the initial phase. OBJECTIVE: This study aims to identify clinically meaningful participant subgroups based on longitudinal adherence to SM of diet, activity, and weight over 6 months as well as psychological predictors of participant subgroups from a self-determination theory (SDT) perspective. METHODS: This was a secondary data analysis of a 6-month digital lifestyle intervention for adults with overweight or obesity. The participants were instructed to perform daily SM on 3 targets: diet, activity, and weight. Data from 50 participants (mean age: 53.0, SD 12.6 y) were analyzed. Group-based multitrajectory modeling was performed to identify subgroups with distinct trajectories of SM adherence across the 3 SM targets. Differences between subgroups were examined for changes in clinical outcomes (ie, body weight, hemoglobin A1c) and SDT constructs (ie, eating-related autonomous motivation and perceived competence for diet) over 6 months using linear mixed models. RESULTS: Two distinct SM trajectory subgroups emerged: the Lower SM group (21/50, 42%), characterized by all-around low and rapidly declining SM, and the Higher SM group (29/50, 58%), characterized by moderate and declining diet and weight SM with high activity SM. Since week 2, participants in the Lower SM group exhibited significantly lower levels of diet (P=.003), activity (P=.002), and weight SM (P=.02) compared with the Higher SM group. In terms of clinical outcomes, the Higher SM group achieved a significant reduction in body weight (estimate: -6.06, SD 0.87 kg; P<.001) and hemoglobin A1c (estimate: -0.38, SD 0.11%; P=.02), whereas the Lower SM group exhibited no improvements. For SDT constructs, both groups maintained high levels of autonomous motivation for over 6 months. However, the Lower SM group experienced a significant decline in perceived competence (P=.005) compared with the Higher SM group, which maintained a high level of perceived competence throughout the intervention (P=.09). CONCLUSIONS: The presence of the Lower SM group highlights the value of using longitudinal SM adherence trajectories as an intervention response indicator. Future adaptive trials should identify nonresponders within the initial 2 weeks based on their SM adherence and integrate intervention strategies to enhance perceived competence in diet to benefit nonresponders. TRIAL REGISTRATION: ClinicalTrials.gov NCT05071287; https://clinicaltrials.gov/study/NCT05071287. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1016/j.cct.2022.106845.

The Impact of Digital Self-Monitoring of Weight on Improving Diabetes Clinical Outcomes: Quasi-Randomized Study.

BACKGROUND: The management of type 2 diabetes (T2D) and obesity, particularly in the context of self-monitoring, remains a critical challenge in health care. As nearly 80% to 90% of patients with T2D have overweight or obesity, there is a compelling need for interventions that can effectively manage both conditions simultaneously. One of the goals in managing chronic conditions is to increase awareness and generate behavioral change to improve outcomes in diabetes and related comorbidities, such as overweight or obesity. There is a lack of real-life evidence to test the impact of self-monitoring of weight on glycemic outcomes and its underlying mechanisms. OBJECTIVE: This study aims to assess the efficacy of digital self-monitoring of weight on blood glucose (BG) levels during diabetes management, investigating whether the weight changes may drive glucose fluctuations. METHODS: In this retrospective, real-world quasi-randomized study, 50% of the individuals who regularly used the weight monitoring (WM) feature were propensity score matched with 50% of the users who did not use the weight monitoring feature (NWM) based on demographic and clinical characteristics. All the patients were diagnosed with T2D and tracked their BG levels. We analyzed monthly aggregated data 6 months before and after starting their weight monitoring. A piecewise mixed model was used for analyzing the time trajectories of BG and weight as well as exploring the disaggregation effect of between- and within-patient lagged effects of weight on BG. RESULTS: The WM group exhibited a significant reduction in BG levels post intervention (P<.001), whereas the nonmonitoring group showed no significant changes (P=.59), and both groups showed no differences in BG pattern before the intervention (P=.59). Furthermore, the WM group achieved a meaningful decrease in BMI (P<.001). Finally, both within-patient (P<.001) and between-patient (P=.008) weight variability was positively associated with BG levels. However, 1-month lagged back BMI was not associated with BG levels (P=.36). CONCLUSIONS: This study highlights the substantial benefits of self-monitoring of weight in managing BG levels in patients with diabetes, facilitated by a digital health platform, and advocates for the integration of digital self-monitoring tools in chronic disease management. We also provide initial evidence of testing the underlying mechanisms associated with BG management, underscoring the potential role of patient empowerment.

Effectiveness of an Artificial Intelligence-Assisted App for Improving Eating Behaviors: Mixed Methods Evaluation.

BACKGROUND: A plethora of weight management apps are available, but many individuals, especially those living with overweight and obesity, still struggle to achieve adequate weight loss. An emerging area in weight management is the support for one's self-regulation over momentary eating impulses. OBJECTIVE: This study aims to examine the feasibility and effectiveness of a novel artificial intelligence-assisted weight management app in improving eating behaviors in a Southeast Asian cohort. METHODS: A single-group pretest-posttest study was conducted. Participants completed the 1-week run-in period of a 12-week app-based weight management program called the Eating Trigger-Response Inhibition Program (eTRIP). This self-monitoring system was built upon 3 main components, namely, (1) chatbot-based check-ins on eating lapse triggers, (2) food-based computer vision image recognition (system built based on local food items), and (3) automated time-based nudges and meal stopwatch. At every mealtime, participants were prompted to take a picture of their food items, which were identified by a computer vision image recognition technology, thereby triggering a set of chatbot-initiated questions on eating triggers such as who the users were eating with. Paired 2-sided t tests were used to compare the differences in the psychobehavioral constructs before and after the 7-day program, including overeating habits, snacking habits, consideration of future consequences, self-regulation of eating behaviors, anxiety, depression, and physical activity. Qualitative feedback were analyzed by content analysis according to 4 steps, namely, decontextualization, recontextualization, categorization, and compilation. RESULTS: The mean age, self-reported BMI, and waist circumference of the participants were 31.25 (SD 9.98) years, 28.86 (SD 7.02) kg/m2, and 92.60 (SD 18.24) cm, respectively. There were significant improvements in all the 7 psychobehavioral constructs, except for anxiety. After adjusting for multiple comparisons, statistically significant improvements were found for overeating habits (mean -0.32, SD 1.16; P<.001), snacking habits (mean -0.22, SD 1.12; P<.002), self-regulation of eating behavior (mean 0.08, SD 0.49; P=.007), depression (mean -0.12, SD 0.74; P=.007), and physical activity (mean 1288.60, SD 3055.20 metabolic equivalent task-min/day; P<.001). Forty-one participants reported skipping at least 1 meal (ie, breakfast, lunch, or dinner), summing to 578 (67.1%) of the 862 meals skipped. Of the 230 participants, 80 (34.8%) provided textual feedback that indicated satisfactory user experience with eTRIP. Four themes emerged, namely, (1) becoming more mindful of self-monitoring, (2) personalized reminders with prompts and chatbot, (3) food logging with image recognition, and (4) engaging with a simple, easy, and appealing user interface. The attrition rate was 8.4% (21/251). CONCLUSIONS: eTRIP is a feasible and effective weight management program to be tested in a larger population for its effectiveness and sustainability as a personalized weight management program for people with overweight and obesity. TRIAL REGISTRATION: ClinicalTrials.gov NCT04833803; https://classic.clinicaltrials.gov/ct2/show/NCT04833803.